Noise reduction (NR) in image sequences can improve both image quality and performance of subsequent video coding. This is so because noise in image sequences adds spurious uncorrelated image components which are visually offensive and which may reduce the effectiveness of any compression scheme which relies on image correlations from frame to frame.
As set forth in a book by J. S. Lim, entitled Two Dimensional Signal and Image Processing, Prentice Hall, 1990, pages 568 et seq., one simple method for performing temporal filtering is through frame averaging. Frame averaging is very effective in processing a sequence of image frames which are contaminated by random noise but in which there is not much change in image information from frame to frame.
As is well known in the art, there are many different ways of performing freune averaging. Although frame averaging may be very simple and effective, precise signal registration from frame to frame is essential for success. In practical applications such as motion pictures and television, the image may change from frame to frame. Parts of the image may move by translation or rotation, by changing in size or by combinations of the above. In some prior-art systems, frame averaging is only applied to still areas of an image, that is to say, to those areas which do not exhibit motion from frame to frame. Other prior-art systems attempt to estimate the movement of an image from one frame to the next and to compensate for this motion in applying frame averaging using respectively different parts of two frames, based on the estimated motion. In order to perform this motion-compensated image restoration, the portions of the image frames are averaged along approximate motion trajectories.
One exemplary noise reduction system is described in my paper entitled "Noise Reduction Using Multi-Frame Motion Estimation, with Outlier Rejection and Trajectory Correction," IEEE Internatinal Conference on Acoustics, Speech and Signal Processing, Apr. 27, 1993, pp V-205 to V-208. This paper describes a video noise reduction system in which image noise is reduced on a pixel-by-pixel basis by calculating a block motion vector and then generating a corrected trajectory for each pixel on a frame-to-frame basis to locate closely corresponding pixel values in each of a plurality of successive image frames. A noise reduced image is then generated by averaging all of the pixel values on the corrected trajectory. This paper also describes a breakdown detection and correction method which inhibits replacement of an original pixel value with a noise-reduced pixel value in certain conditions.
An alternative way of accomplishing noise reduction is disclosed by an article by T. J. Dennis entitled, "Nonlinear Temporal Filter For Television Picture Noise Reduction," IEEE Proceedings, Vol. 127, Pt. G, No. 2, April 1980, pages 52 et seq. Specifically, a conventional recursive interframe low pass filter for a 625 line 5.5 MHz monochrome television is modified so that any attenuation of frame differences is instantaneously dependent on the amplitude of the frame differences. Thus, the filter attenuates large area spatial interference, such as streaking, provided it does not contain zero frequency or frame frequency components. Using this method, however, some spatial degradation may occur in areas of the image which contain motion.
A further technique to accomplish noise reduction is disclosed by an article by E. Dubois et al. entitled, "Noise Reduction in Image Sequences Using Motion-Compensated Temporal Filtering," IEEE Transactions on Communications, Vol. COM-32, No. 7, July 1984, pages 826 et seq. In particular, the nonlinear recursive filtering approach is extended by the application of motion-compensation techniques. Furthermore, a specific noise reducer for use with NTSC composite television signals is disclosed. Unlike prior low order non-recursive filters, the nonlinear recursive filtering approach described by Dubois is able to reduce noise to a greater extent than prior art noise reduction systems. There are, however, practical limitations on the ability of the circuit to effectively reduce various types of noise.
Yet another method of image noise reduction is described in a paper by T. A. Reinen entitled "Noise Reduction in Heart Movies by Motion Compensated Filtering" SPIE vol 1606 Visual Communications and Image Processing '91: Image Processing July, 1991, pp 755-763. This paper describes a method of using motion compensated temporal filtering for removing noise in medical image sequences. This method employs a first order recursive filter adapts automatically to the quality of motion estimation to produce an edge preserving spatial filter.